ALGORITHMIC MANAGEMENT IN THE WORKPLACE: A DUAL-PATHWAY MODEL FOR HR GOVERNANCE, EMPLOYEE AUTONOMY, AND ETHICAL IMPLEMENTATION

Abstract

The rapid adoption of algorithmic management and AI-driven decision-making is reshaping human resource management and workplace dynamics. While these technologies enhance efficiency, consistency, and data-driven insights, they also raise critical concerns regarding employee autonomy, trust, and ethical governance. This article develops a dual-pathway model that integrates HR governance and employee autonomy to address these challenges. Drawing on a conceptual and qualitative review of literature on algorithmic management, HR governance, and workplace ethics, the study identifies two complementary pathways: a governance pathway focused on compliance, transparency, and accountability, and an autonomy pathway emphasizing empowerment, flexibility, and human–AI collaboration. The findings highlight that balancing these pathways is essential to mitigate risks such as bias, over-surveillance, and reduced employee agency while maximizing organizational performance and engagement. The model also underscores the importance of managing inherent tensions between efficiency and autonomy, as well as control and trust. By providing a structured framework, the study contributes to the discourse on responsible AI and ethical HR practices. It concludes that organizations must adopt integrated, human-centered approaches to algorithmic management to ensure sustainable, fair, and effective workplace outcomes.